1. Field of the Invention
The present invention is related to language dialog systems and, more particularly to domain model creation for natural language dialog systems.
2. Background Description
In the development of spoken or natural language dialog systems, a representation, referred to as a domain model, is used in the creation of grammars, dialog managers and other system components. The domain model provides a useful, formalized representation of knowledge about the domain of an application that the system is addressing and reflects a particular domain expert""s conceptualization of that knowledge.
Previously, domain models were handcrafted by the particular domain expert and crafting required substantial time and specialized expertise. Model development focus was directed to the acquisition of procedural knowledge for use by expert systems. Such knowledge was acquired and maintained in the form of rules for encoding instructions. The instructions were provided to the expert system and were the selected response for performing a given action under a given set of conditions. These methods all require a substantial amount of an expert""s time.
To that end, tools are being developed to facilitate domain model development. One such tool is the LOOM knowledge representation system from Sun Microsystems which is a toolkit for the development of domain models by domain experts. A state of the art project that is based on LOOM is a domain model development toolkit called EXPECT. EXPECT uses the LOOM framework to construct domain models and provide an intuitive interface. However, to use EXPECT a domain expert must construct the ontology of the domain from scratch.
Typically, the goal in expert systems is to capture an expert""s knowledge in computer usable form. In particular procedural knowledge is captured and used for predicting likely responses in particular given situations, such as how to diagnose a disease or how to effect auto repairs. Declarative knowledge is required to create grammars and other spoken dialog components used in spoken language dialog expert systems.
However, in creating spoken language dialog components for such systems, domain models are not explicitly created and, instead, grammars or speech models are induced directly. This direct induction approach requires inputting a corpus of training examples. In grammar development, the input corpus must be annotated for semantics. Such corpora are expensive, difficult to obtain and, their size and quality directly affects the quality of the resulting system, i.e., larger, higher quality and correspondingly more difficult to obtain and so more expensive corpora yield a higher quality spoken language dialog system.
Because of their many advantages, spoken language dialog systems development is an active area of current research and promises many products with a variety of applications. Such products may be used for receiving stock quotes, disseminating weather or yellow pages information, sending and receiving e-mail, as well as using a voice interface to browse the Internet. The main hurdle in getting new products to market is the time and expertise required to create or adapt necessary spoken dialog components, such as grammars, speech recognizers and dialog managers for new domains. Whoever can best streamline the process of porting these components to new domains will have a distinct advantage over others in this competitive field.
Thus, there is a need for an easy way to automatically create declarative domain information in a form that reflects a domain expert""s conceptualization of the domain.